Fluorescent image analyzer, analyzing method, and pretreatment evaluation method

ABSTRACT

A fluorescence image analyzer, analyzing method, and pretreatment evaluation method capable of determining with high accuracy whether a sample is positive or negative are provided. A pretreatment part performs pretreatment including a step of labeling a target site with a fluorescent dye to prepare a sample. A fluorescence image analyzer measures and analyzes the sample. The fluorescent image analyzer includes light sources to irradiate light on the sample, imaging part to capture the fluorescent light given off from the sample irradiated by light, and processing part for processing the fluorescence image captured by the imaging part. The processing part extracts the bright spot of fluorescence generated from the fluorescent dye that labels the target site from the fluorescence image for each of a plurality of cells included in the sample, and generates information used for determining whether the sample is positive or negative based on the bright spots extracted for each of the plurality of cells.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/608,380, filed on May 30, 2017, entitled “FLUORESCENT IMAGE ANALYZER,ANALYZING METHOD, AND PRETREATMENT EVALUATION METHOD,” which claimspriority from prior Japanese Patent Application No. 2016-109005, filedon May 31, 2016, entitled “FLUORESCENT IMAGE ANALYZER AND PRETREATMENTEVALUATION METHOD,” and prior Japanese Patent Application No.2017-045666, filed on Mar. 10, 2017, entitled “FLUORESCENT IMAGEANALYZER, ANALYZING METHOD, AND PRETREATMENT EVALUATION METHOD,” theentire contents of each of which are incorporated herein by reference.

FIELD OF THE INVENTION

The invention relates to a fluorescent image analyzer, analyzing method,and pretreatment evaluation method.

BACKGROUND

Japanese Patent Application Publication No. 2005-515408 describes a celltreatment method when a flow cytometer or the like is applied fordetection by the fluorescence in situ hybridization method (FISHmethod). According to the FISH method, cells are stained by pretreatmentin which a labeled probe is hybridized with a DNA sequence region to bedetected in a cell, and the fluorescence generated due to the labeledprobe is detected so as to detect the abnormal cells.

SUMMARY OF THE INVENTION

For example, it is necessary to detect abnormal cells by observing ahuge number of cells such as 1,000 to 10,000 cells when trying toaccurately determine whether the collected sample is positive ornegative for a specific disease using the above-described method fordetecting abnormal cells. In this case, it becomes difficult to maintainthe accuracy of determining whether the sample is positive or negativebecause the burden increases on the operator detecting abnormal cells,and the detection of abnormal cells depends on the senses of theoperator.

A first aspect of the invention relates to a fluorescence image analyzerfor carrying out a pretreatment including a step of labeling a targetsite with a fluorescent dye and measuring and analyzing the preparedsample. The fluorescence image analyzer of this aspect includes lightsources to irradiate light on the sample, an imaging part to capture thefluorescent light given off from the sample irradiated by light, and aprocessing part for processing the fluorescence image captured by theimaging part. The processing part extracts the bright spot offluorescence generated from the fluorescent dye that labels the targetsite from the fluorescence image for each of a plurality of cellsincluded in the sample, and generates information used for determiningwhether the sample is positive or negative based on the bright spotsextracted for each of the plurality of cells.

A second aspect of the invention relates to a fluorescence imageanalyzer for carrying out a pretreatment including a step of labeling atarget site with a fluorescent dye and measuring and analyzing theprepared sample. The fluorescence image analyzer of this aspect includeslight sources to irradiate light on the sample, an imaging part tocapture the fluorescent light given off from the sample irradiated bylight, and a processing part for processing the fluorescence imagecaptured by the imaging part. The processing part extracts the brightspot of fluorescence generated from the fluorescent dye that labels thetarget site from the fluorescence image for each of a plurality of cellsincluded in the sample, and generates information used for determiningwhether the sample is positive or negative based on the bright spotsextracted for each of the plurality of cells.

A third aspect of the invention relates to analyzing method foranalyzing a sample prepared in a pretreatment including a step oflabeling a target site with a fluorescent dye. The analyzing method ofthis aspect includes a step of irradiating light on a sample prepared inpretreatment, a step of imaging fluorescence given off from the sampleirradiation with light, a step of extracting a bright spot offluorescence produced by the fluorescent dye labeling the target sitefrom the fluorescence image for each of a plurality of cells included inthe sample, and a step of generating information used to determinewhether the sample is positive or negative based on the bright spotsextracted for each of the plurality of cells.

A fourth aspect of the invention is an analyzing method for samplesincluding a plurality of cells having a target site labeled with afluorescent dye. The analyzing method of this aspect includes a step ofextracting a pattern of bright spots of fluorescence generated from afluorescent dye from each fluorescence image of a plurality of cells, astep of classifying each of the plurality of cells based on a pattern ofbright spots, and a step of generating information used for determiningwhether the sample is positive or negative based on the classificationresult of the cells.

A fifth aspect of the invention relates to a fluorescence image analyzerfor carrying out a pretreatment including a step of labeling a targetsite with a fluorescent dye and measuring and analyzing the preparedsample. The fluorescence image analyzer of this aspect includes lightsources to irradiate light on the sample, an imaging part to capture thefluorescent light given off from the sample irradiated by light, and aprocessing part for processing the fluorescence image captured by theimaging part. The processing part extracts a bright spot of fluorescencegenerated from the fluorescent dye that labels the target site from thefluorescence image, acquires an index reflecting the state of the brightspot based on the extracted bright spot, and determines whetherpretreatment is appropriate based on the acquired index.

A sixth aspect of the invention relates to a fluorescence image analyzerfor carrying out a pretreatment including a step of labeling a targetsite with a fluorescent dye and measuring and analyzing the preparedsample. The fluorescence image analyzer of this aspect includes lightsources to irradiate light on the sample, an imaging part to capture thefluorescent light given off from the sample irradiated by light, and aprocessing part for processing the fluorescence image captured by theimaging part. The processing part extracts a bright spot of fluorescencegenerated from the fluorescent dye that labels the target site from thefluorescence image, acquires an index reflecting the state of the brightspot based on the extracted bright spot, and causes information based onthe acquired index to be shown on the display part.

A seventh aspect of the invention is an evaluation method forpretreatment of cell analysis including a step of labeling a target sitewith a fluorescent dye. The evaluation method for pretreatment of thisaspect includes a step of irradiating light on a sample prepared in thepretreatment, a step of capturing the fluorescence generated from thesample irradiated with light, a step of extracting the bright spot offluorescent light generated from the fluorescent dye that labels thetarget site from the fluorescence image, a step of acquiring an indexreflecting the state of the bright point based on the extracted brightspot.

According to the invention, whether a sample is positive or negative canbe determined with high accuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically shows the structures of the fluorescence imageanalyzer and pretreatment part of the embodiment;

FIG. 2A shows an example of first through third images and a brightfield image acquired by the fluorescence image analyzer of theembodiment;

FIG. 2B illustrates the extraction of a nucleus region performed by thefluorescence image analyzer of the embodiment;

FIGS. 2C and 2D illustrate the extraction of a bright spot regionperformed by the fluorescence image analyzer of the embodiment;

FIGS. 3A through 3D schematically show respective examples of the brightspot arrangements of a negative pattern, positive pattern 1, positivepattern 2, and positive pattern 3 of the embodiment;

FIG. 4 illustrates a first index of the embodiment;

FIG. 5 illustrates a second index of the embodiment;

FIG. 6 illustrates a third index of the embodiment;

FIG. 7 illustrates a third index of the embodiment;

FIG. 8 illustrates a fourth index of the embodiment;

FIG. 9 illustrates a fifth index of the embodiment;

FIG. 10 illustrates a sixth index of the embodiment;

FIG. 11A is a flow chart showing the process of displaying thedetermination results of whether pretreatment is appropriate accordingto the first embodiment;

FIG. 11B schematically shows the structure of a screen displayed on thedisplay part of the first embodiment;

FIG. 12A is a flow chart showing the process of displaying the analysisresults of the first embodiment;

FIG. 12B schematically shows the structure of a screen displayed on thedisplay part of the first embodiment;

FIG. 13A is a flow chart showing the process of displaying thedetermination results of whether pretreatment is appropriate and theanalysis results according to a second embodiment;

FIG. 13B schematically shows the structure of a screen displayed on thedisplay part of the second embodiment;

FIG. 14A and FIG. 14B conceptually show the structure of a databasestored in the memory part of a third embodiment;

FIG. 15A is a flow chart showing the process of displaying thedetermination results of whether pretreatment is appropriate accordingto the third embodiment;

FIG. 15B schematically shows the structure of a screen displayed on thedisplay part of the third embodiment;

FIG. 16A is a flow chart showing the process of displaying thedetermination results of whether pretreatment is appropriate accordingto a fourth embodiment; FIG. 16B schematically shows the structure of ascreen displayed on the display part of the fourth embodiment;

FIG. 17 schematically shows the structure of a screen displayed on thedisplay part of a fifth embodiment;

FIG. 18 schematically shows the structure of the imaging part of a sixthembodiment;

FIG. 19 schematically shows the structure of the fluorescence imageanalyzer of a seventh embodiment;

FIG. 20A schematically shows the bright spot patterns stored in thememory part and the determinations associated with the bright spotpatterns of an eighth embodiment; and

FIG. 20B schematically shows the structure of a screen displayed on thedisplay part of the eighth embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following embodiment is an application of the present inventionapplied to an apparatus for measuring and analyzing a sample prepared ina pretreatment including a step of hybridizing a nucleic acid probelabeled with a fluorescent dye and a target site in a nucleic acid.Specifically, in the following embodiment, the target site in thenucleic acid is the BCR gene on chromosome 22 and the ABL gene onchromosome 9, and cells with translocation between chromosome 22 andchromosome 9 found in chronic myeloid leukemia are detected as abnormalcells based on the FISH method. That is, in the following embodiment, acell in which a BCR gene or ABL gene is translocated to generate aBCR-ABL fusion gene is detected as an abnormal cell. In the followingembodiments, the cells to be detected are white blood cells in the bloodsample.

Apparatus Structure

As shown in FIG. 1, the fluorescence image analyzer 10 measures andanalyzes a sample 20 a prepared by pretreatment by the pretreatment part20. The operator performs processing such as centrifugal separation onblood specimens collected from a subject and extracts leukocytes asdetection target cells. In the extraction of white blood cells,leukocytes may be extracted by hemolyzing other blood cells with ahemolytic agent instead of centrifugation. The pretreatment part 20includes a mixing container for mixing the reagent and the samplesubjected to treatment such as centrifugal separation, a dispensing partfor dispensing the sample and reagent to the mixing container, and aheating part to heat the mixing container. The pretreatment part 20carries out a pretreatment including a step of labeling the target siteof the detection target cells collected from the subject with thefluorescent dye, and a step of specifically staining the nucleus of thecell with the dye by nuclear staining to prepare sample 20 a.Specifically, in the step of labeling the target site with thefluorescent dye, a nucleic acid probe labeled with the fluorescent dyeand the target site in the nucleic acid are hybridized.

The nucleic acid probe that hybridizes with the BCR gene is labeled witha first fluorescent dye that produces fluorescence with a wavelength λ21upon irradiation with excitation light of wavelength λ11. In this waythe BCR gene is labeled with the first fluorescent dye. The nucleic acidprobe that hybridizes with the ABL gene is labeled with a secondfluorescent dye that produces fluorescence with a wavelength λ22 uponirradiation with excitation light of wavelength λ12. In this way the ABLgene is labeled with the second fluorescent dye. The nucleus is dyedwith a dye for nuclear staining which produces fluorescence ofwavelength λ23 by irradiation with excitation light of wavelength λ13.

More specifically, the pretreatment part 20 includes a treatment forimmobilizing the cells so that the cells do not contract due todehydration, a membrane permeation treatment for opening a hole of asize sufficient to introduce the nucleic acid probe into the cell, aheat denaturation treatment to add heat to the cells, a treatment ofhybridizing a target site and a nucleic acid probe, a washing treatmentto remove unnecessary nucleic acid probe from a cell, and a treatment tostain a nucleus.

The fluorescence image analyzer 10 includes an imaging unit 100, aprocessing part 11, a memory part 12, a display part 13, and an inputpart 14. The imaging unit 100 includes a flow cell 110, light sources121 to 124, condenser lenses 131 to 134, dichroic mirrors 141 and 142, acondenser lens 151, an optical unit 152, a condenser lens 153, animaging part 154. The sample 20 a flows through the flow path 111 of theflow cell 110.

The light sources 121 to 124 irradiate light on the sample 20 a flowingthrough the flow cell 110. The light sources 121 to 124 are configuredby a semiconductor laser light source. The light emitted from therespective light sources 121 to 124 is laser light of wavelengths λ11 toλ14. The condenser lenses 131 to 134 condense the light from therespective light sources 121 to 124. The dichroic mirror 141 transmitslight of wavelength λ11 and reflects light of wavelength λ12. Thedichroic mirror 142 transmits light of wavelength λ11 and λ12, andreflects light of wavelength λ13. Thus, the light of wavelengths λ11 toλ14 irradiate the sample flowing through the flow path 111 of the flowcell 110.

When the sample flowing through the flow cell 110 is irradiated withlight having wavelengths λ11 to λ13, fluorescence is given off from thefluorescent dye staining the cells. Specifically, when the firstfluorescent dye that labels the BCR gene is irradiated by light ofwavelength λ11, fluorescence of wavelength λ21 is given off from thefirst fluorescent dye. When the second fluorescent dye that labels theABL gene is irradiated by light of wavelength λ12, fluorescence ofwavelength λ22 is given off from the second fluorescent dye. When thedye for nuclear staining which stains the nucleus is irradiated by lightof the wavelength λ13, fluorescence of wavelength λ23 is given off fromthe dye for nuclear staining. When the sample flowing through the flowcell 110 is irradiated with light of wavelength λ14, this lighttransmits through the cell. The light of wavelength λ14 that has passedthrough the cell is used for generating a bright field image. In theembodiment, the wavelength λ21 is a wavelength band of green light,wavelength λ22 is a wavelength band of red light, and wavelength λ23 isa wavelength band of blue light.

The condensing lens 151 collects the fluorescence of wavelengths λ21 toλ23 generated from the sample flowing through the flow channel 111 ofthe flow cell 110, and the light of wavelength λ14 transmitted throughthe sample flowing through the flow channel 111 of the flow cell 110. Anoptical unit 152 has a configuration combining four dichroic mirrors.The four dichroic mirrors of the optical unit 152 reflect thefluorescence of the wavelengths λ21 to λ23 and the light of thewavelength λ14 at slightly different angles from each other andseparates them on the light receiving surface of the imaging part 154.The condenser lens 153 condenses the fluorescent light of wavelengthsλ21 to λ23, and the light of wavelength λ14.

The imaging part 154 is configured by a TDI (Time Delay Integration)camera. The imaging part 154 captures the fluorescence of thewavelengths λ21 to λ23 and the light of the wavelength λ14 and outputsthe fluorescence image corresponding to the respective fluorescencelights of wavelengths λ21 to λ23 and the bright field imagecorresponding to the light of wavelength λ14 as image signals.Fluorescent images corresponding to the fluorescence of wavelengths λ21to λ23 are hereinafter referred respectively to as “first image”,“second image”, and “third image”.

In the example of FIG. 2A, bright spots of fluorescence of wavelengthλ21 are distributed in black dots in the first image, and bright spotsof fluorescence of wavelength λ22 are distributed in black dots in thesecond image, albeit somewhat thinner compared to the first image. Inthe third image, the nuclear region is distributed in black. In thebright-field image, the actual state of the cell can be verified. Notethat each image in FIG. 2A is an image showing, as an example, a sampleobtained by placing white blood cells after pretreatment on a slideglass and observing with a microscope, and the first to third images inFIG. 2A are obtained by inverting the gradation and then changing thecolor tone to gray. In the case where the sample 20 a flowing throughthe flow cell 110 is imaged by the imaging part 154 as described above,the sample 20 a flows through the flow path 111 with the cells mutuallyseparated from each other, so that the fluorescence images and thebright field image are obtained for each cell.

Returning to FIG. 1, the processing part 11 is configured by a CPU. Theprocessing part 11 also may be configured by a CPU and microcomputer.The processing part 11 performs processing of various types based on aprogram stored in the memory part 12. The processing part 11 isconnected to the imaging unit 100, memory part 12, display part 13, andinput part 14, receives signals from each part, and controls each part.The memory part 12 is configured by RAM, ROM, hard disk or the like. Thedisplay part 13 is configured by a display. The input part 14 isconfigured by a mouse and keyboard.

The processing part 11 processes the first to third images captured bythe imaging part 154. Specifically, the processing part 11 extractsbright spots of fluorescence of wavelength λ21 from the first imagebased on the fluorescent light of wavelength λ21, and extracts brightspots of fluorescence of wavelength λ22 from the second image based onthe fluorescent light of wavelength λ22. The processing part 11 alsoextracts the nuclear region from the third image based on thefluorescent light of wavelength λ23.

The processing part 11 detects abnormal cells by determining whether theBCR gene or the ABL gene is a translocated abnormal cell for each cellbased on the distribution status of the bright spots in the first imageand the second image. The determination of the abnormal cell isdescribed below referring to FIGS. 3A to 3D.

The processing part 11 also generates information used for determiningwhether the sample 20 a is positive or negative based on the brightspots extracted for each of a plurality of cells. According to the aboveconfiguration, it is unnecessary for the operator to observe an enormousnumber of cells to detect abnormal cells, and detection of abnormalcells does not depend on the sense of the operator, so that thedetection accuracy of abnormal cells is enhanced. Therefore, theaccuracy of the information used for determining whether the sample 20 ais positive or negative is increased, so that the physician candetermine whether the sample 20 a is positive or negative with highaccuracy by referring to this information. This information is describedbelow referring to FIG. 20B.

The extraction of the nucleus region and the extraction of the brightspot region performed by the fluorescence image analyzer 10 will bedescribed next.

The third image shown at the left end of FIG. 2B, the first image shownat the left end of FIG. 2C, and the second image shown at the left endof FIG. 2D are acquired from the same region of sample 20 a flowingthrough the flow cell 110.

When the third image is acquired as shown at the left end of FIG. 2B,the processing part 11 generates a graph of brightness and degree asshown in the center of FIG. 2B based on the brightness of each pixel onthe third image. The degree of the vertical axis indicates the number ofpixels. The processing part 11 sets the brightness threshold in thisgraph. The processing part 11 then extracts the range in which thepixels having a brightness larger than the threshold value aredistributed as the nucleus region as indicated by the broken line at theright end of FIG. 2B Note that in the third image, when two nucleioverlap each other, the first to third images relating to the overlappedcells are excluded and are not used for determination of appropriatenessof pretreatment and determination of abnormal cells.

When the first image is acquired as shown at the left end of FIG. 2C,the processing part 11 generates a graph of brightness and degree asshown in the center of FIG. 2C based on the brightness of each pixel onthe first image. In this graph, the processing part 11 sets a thresholdof brightness, for example, as a boundary between the bright spot andthe background based on the Otsu method. The processing part 11 thenextracts the range in which the pixels having a brightness larger thanthe threshold value are distributed as the bright spot region asindicated by the broken line at the right end of FIG. 2C. Note that whena bright spot region is extracted from the first image, a bright spothaving an extremely small region, a bright spot having an extremelylarge region, and a bright spot not included in the nuclear region shownat the right end of FIG. 2B are excluded.

When the second image is acquired as shown at the left end of FIG. 2D,the processing part 11 generates a graph of brightness and degree asshown in the center of FIG. 2D based on the brightness of each pixel onthe second image. The processing part 11 then sets the brightnessthreshold value in the graph, and extracts the range in which the pixelshaving a brightness larger than the threshold value are distributed asthe bright spot region as indicated by the broken line at the right endof FIG. 2D. Note that when a bright spot region is extracted from thesecond image, a bright spot having an extremely small region, a brightspot having an extremely large region, and a bright spot not included inthe nuclear region shown at the right end of FIG. 2B are excluded.

Note that the processing part 11 also may extract a nuclear region fromthe third image, and extract the bright spot region from the first imageand the second image by calculation according to the procedure describedabove without preparing a graph as shown in the center of FIGS. 2B to2D. The extraction of the bright spots also may be performed bydetermining the degree of matching between the distribution waveform ofthe normal bright spots and the region to be determined, and extractingthe region to be determined as a bright spot when the degree of matchingis high. Although the processing part 11 detects cells by extracting anucleus region from the third image, cells also may be detected based onthe bright field image. In the case where cells are detected based onthe bright field image, acquisition of the third image can be omitted.Bright spot in the present embodiment means a point of smallfluorescence generated in the fluorescence image. More specifically,bright spot means the point of fluorescence obtained from thefluorescent dye of the nucleic acid probe bound to the gene of thetarget site in the nucleus.

Determination of abnormal cells performed by the fluorescence imageanalyzer 10 will be described below referring to FIGS. 3A to 3D.

FIG. 3A shows an arrangement example of the bright spots of the negativepattern, and FIGS. 3B to 3D show arrangement examples of the brightspots of the positive patterns 1 to 3. Note that, in this embodiment,the arrangement pattern of the bright spots in the abnormal cellsubstantially coincides with any one of the positive patterns 1 to 3shown in FIGS. 3B to 3D.

As shown in FIG. 3A, when no translocation occurs for the BCR gene andthe ABL gene, there are two bright spots of fluorescence with wavelengthλ21, that is, green fluorescent light in the nucleus in the first image,and there are two bright spots of fluorescence of wavelength λ22, thatis, red fluorescent light in the nucleus in the second image. In thiscase, when the first image and the second image are combined, two greenbright spots and two red bright spots exist in one nucleus in thecomposite image. In this way, when each bright spot exists as shown inFIG. 3A, the processing part 11 determines that translocation does notoccur for the BCR gene and the ABL gene of this cell, that is, the cellis negative.

As shown in FIG. 3B, when a part of the ABL gene has moved to chromosome9 due to translocation, there are two points of green fluorescencebright spots in the nucleus in the first image, and there are three redpoints in the nucleus of red fluorescence in the second image. In thiscase, when the first image and the second image are combined, one greenbright spot, two red bright spots, and one yellow bright spot exist inone nucleus in the composite image. When each bright spot exists asshown in FIG. 3B, the processing part 11 determines that translocationoccurs for the BCR gene and the ABL gene of this cell, that is, the cellis positive.

As shown in FIG. 3C, when a part of the BCR gene is transferred tochromosome 22 by a translocation and a part of the ABL gene istransferred to chromosome 9, three points of green fluorescence occur inthe nucleus in image 1, and three points of red fluorescence lightsoccur in the nucleus in the second image. In this case, when the firstimage and the second image are combined, one green bright spot, one redbright spot, and two yellow bright spots exist in one nucleus in thecomposite image. When each bright spot exists as shown in FIG. 3C, theprocessing part 11 determines that translocation occurs for the BCR geneand the ABL gene of this cell, that is, the cell is positive.

As shown in FIG. 3D, when the ABL gene has moved to chromosome 9 due totranslocation, there are two points of green fluorescence bright spotsin the nucleus in the first image, and there are two points of redfluorescence bright spots in the nucleus in the second image. In thiscase, when the first image and the second image are combined, one greenbright spot, one red bright spot, and one yellow bright spot exist inone nucleus in the composite image. When each bright spot exists asshown in FIG. 3D, the processing part 11 determines that translocationoccurs for the BCR gene and the ABL gene of this cell, that is, the cellis positive.

When labeling, with fluorescent dye, a target site of a nucleic acidsequence region to be detected, in the pretreatment, for example, it isnecessary to perform complex steps such as a treatment to apply heat tothe cell, treatment for hybridizing a nucleic acid probe to the targetsite, treatment to remove unnecessary nucleic acid probe from the celland the like. In each step of the pretreatment, there is concern thatonly a slight change in the treatment temperature, treatment time,reagent concentration, reagent amount and the like may break thechromosome or the target site may not be properly labeled by the nucleicacid probe. Since the analysis is performed by observing the target sitebased on the nucleic acid probe, unless the pretreatment isappropriately performed, there is a possibility that the analysisresults will vary and the reliability of the analysis will be reduced.In addition, when an operator tries to determine the appropriateness ofpretreatment, it is necessary to observe an enormous number of cells,and the suitability determination depends on the feeling of theoperator, which makes it difficult to maintain determination accuracy.

It is possible to deal with the above mentioned problems if thefluorescence image analyzer 10 has the function of determining whetherpretreatment is appropriate.

The processing part 11 of the fluorescence image analyzer 10 determineswhether pretreatment is appropriate by acquiring an index reflecting thestate of the bright spot that changes in accordance with the state ofthe pretreatment based on the extracted bright spot, and comparing theacquired index with a threshold value that classifies whetherpretreatment is appropriate. The determination of the index and whetherpretreatment is appropriate will be described later with reference toFIGS. 4 to 10.

As described above, the fluorescence image analyzer 10 acquires an indexreflecting the state of the bright spot that changes in accordance withthe state of the pretreatment, and whether pretreatment is appropriateis determined based on the acquired index. In this way it is possible todetermine whether pretreatment is appropriate with high accuracy. Inaddition, when pretreatment is inappropriate, it can be an opportunityto make the pretreatment appropriate, such as reviewing the pretreatmentprocedure, so that the reliability of the analysis by the fluorescenceimage analyzer 10 can be enhanced. Compared with a case where thedetermination of the appropriateness of pretreatment is performedthrough the senses of the operator, it is possible to omit the labor ofthe operator and determine pretreatment appropriateness withoutvariability.

The index reflecting the state of a bright spot that changes accordingto the state of pretreatment acquired by the fluorescence image analyzer10 will be described below.

Cases when pretreatment is not performed properly include when a nucleicacid site other than the target site is fluorescently labeled by bindingof a nucleic acid probe to a nucleic acid site other than the targetsite by so-called nonspecific binding, and when the target site is notsufficiently fluorescently labeled due to the lack of binding of thenucleic acid probe to the target site.

The inventors investigated how to properly fluorescently label thetarget site by setting conditions such as temperature and concentration,that is, control factors, when performing the pretreatment. In thisprocess, the inventors found that the state of pretreatment can bedetermined by noticing that when the control factor is changed from thecase where the state of the bright spot is most favorable, the state ofthe bright spot deteriorates, and determining whether the state of thedegree of brightness changed from when the state of the bright spot ismost favorable. Hereinafter, first to sixth indices for determining thestate of pretreatment will be described.

First Index

The first index is an index focusing on the fact that the target site isproperly fluorescently labeled and the number of bright spots in thefirst image and the second image is the presumed number if pretreatmentis properly performed.

As shown in FIG. 4, the inventors performed pretreatment on standardsamples, that is, negative samples, under the pretreatment conditionsNo. 1 to No. 8. Seven control factors A to G are set in pretreatmentconditions No. 1 to No. 8. The seven control factors A to G respectivelyare heat denaturation temperature, heat denaturation time, heatdenaturation method, hybridization temperature, probe amount, washingsolution temperature, and washing solution salt concentration.

Control factor A is the temperature at which nucleic acids and nucleicacid probes are thermally denatured prior to hybridization and the unitsare in degrees Celsius. Control factor B is the time to thermallydenature nucleic acids and nucleic acid probes, and the units areminutes. Control factor C is a method of thermally denaturing nucleicacids and nucleic acid probes. Method 2 is a method in which thermaldenaturation of a nucleic acid and thermal denaturation of a nucleicacid probe are carried out at the same time. Control factor D is thetemperature at which the nucleic acid and the nucleic acid probe arehybridized, and the units are in degrees Celsius. Control factor E isthe magnification of the amount of nucleic acid probe relative to adefined amount. Control factor F is the temperature of the washingsolution for washing the sample after hybridization, and the units aredegrees Celsius. Control factor G is the magnification of the saltconcentration of the washing solution relative to a defined amount.

The inventors pretreated a negative sample under pretreatment conditionsshown in Nos. 1 to 8 to prepare a sample, and measured the preparedsample to obtain first to third images. The inventors then calculatedthe ratio in each number of the number of cells in which the brightspots in the first image and the second image where any of the negativepattern and the positive patterns 1 to 3 changed by dividing the nucleusarea of the image by the number of cells that could be extracted basedon the third image, as shown in FIGS. 3A to 3D. That is, the inventorscalculated the proportion of cells that can be analyzed among thedetected cells. Hereinafter, the ratio of cells that can be analyzedamong the detected cells is referred to as the “first index”. As aresult of verification by the inventors, in the case of number 5, thefirst index was 68%, which was the highest value compared with otherpretreatment conditions.

The inventors determined that the pretreatment condition of number 5 isthe condition that can perform the pretreatment most appropriately, andset a threshold value to determine whether pretreatment is appropriatebased on the value of the first index at this time of 68%. Specifically,the inventors set the threshold value for determining that thepretreatment state is at the warning level to 50%, and set the thresholdvalue for determining that the pretreatment state is at the abnormallevel to 30%. Note that the threshold value of the warning level is setto a value smaller than the value of the first index acquired in thecase where performing pretreatment is considered most appropriate, andthe threshold value of the abnormality level may be set to a value lessthan the threshold value by a predetermined value.

In the pretreatment actually carried out by the inventors shown in FIG.4, cells that can be analyzed are limited to cells of a negative patternsince a negative sample is used. However, when pretreatment is performedusing an actual sample, most cells that can be analyzed become cells ofeither the negative pattern or the positive patterns 1 to 3. Therefore,as described above, the first index calculated by dividing the number ofcells which conform to any of the negative pattern and positive patterns1 to 3 by the number of cells from which the nuclear region can beextracted is not limited to a negative sample, and the first index alsocan be used as an index when pretreatment is appropriate for actualsamples. Cells that can not be analyzed among the detected cells arethose cells that did not correspond to any of the negative pattern andthe positive patterns 1 to 3 because the pretreatment was not properlyperformed.

A procedure for actually determining whether pretreatment is appropriateusing the first index is described below.

First, with a predetermined timing, for example, immediately beforestarting use of the fluorescence image analyzer 10 one day, the operatorpretreats a negative sample which is a standard sample using thepretreatment part 20. The operator then sets the sample 20 a prepared bypretreating the standard sample in the fluorescence image analyzer 10,and measures the sample 20 a. The processing part 11 acquires the firstto third images for each cell and extracts the region of the nucleus andthe region of the bright spot.

The processing part 11 then acquires the number of cells that can beproperly extracted from the nuclear region based on the third image as afirst number, and acquires the number of cells in which bright spots inthe first image and the second image match any of the negative patternand positive patterns 1 to 3 as a second number. Then, the processingpart 11 acquires the ratio of the second number to the first number asthe first index. The processing part 11 compares the threshold valuescorresponding to the warning level and the abnormal level with the firstindex to determine whether pretreatment is appropriate. Specifically,when the first index is less than the warning level but equal to or morethan the abnormal level, the processing part 11 determines that thepretreatment state is the warning level, and when the first index isless than the abnormal level, determines that the pretreatment state isthe abnormal level.

As described above, the threshold value is set based on the first indexat which pretreatment is considered to be most appropriate from theverification result, and the first index actually acquired based on thestandard sample is compared with the set threshold value to determinewhether the pretreatment is appropriate. In this way, when thepretreatment is not properly performed, the value of the actuallyacquired first index becomes smaller than the first index in the casewhere the pretreatment is appropriately performed. Therefore, it ispossible to accurately determine whether pretreatment is appropriate bycomparing the value of the actually acquired first index with thethreshold value.

Note that the appropriateness of pretreatment can be determined evenwhen using a sample 20 a prepared by pretreating the actual samplecollected from the subject, that is, the sample 20 a prepared in thecase of actually performing the analysis. The sample 20 a based on theactual sample includes cells in which the bright spots in the firstimage and the second image are negative patterns shown in FIG. 3A, andcells in which the bright spots are positive pattern 1 shown in FIGS. 3Bto 3D.

In this case, the processing part 11 also acquires the number of cellsin which the bright spots in the first image and the second image matchany of the negative pattern and the positive patterns 1 to 3 as thesecond number. The second number in this case is also the number ofcells that can be analyzed among the detected cells. Therefore, also inthis case, the processing part 11 divides the second number by the firstnumber which is the detected cell number, so that the first index can beset as the same as in the case of the sample 20 a based on the negativesample described above. The processing part 11 then compares theacquired first index with the threshold value of the warning level andthe threshold value of the abnormality level similar to the case of thesample 20 a based on the negative sample described above, and determineswhether pretreatment is appropriate.

Second Index

As described above, when pretreatment is not properly performed, thetarget site may be insufficiently fluorescently labeled in some cases.The second index is an index focusing on the fact that the brightness ofthe bright spots in the first image and the second image decreases whenthe preprocessing is not properly performed. A procedure for actuallydetermining whether pretreatment is appropriate using the second indexis described below.

First, the operator pretreats a negative sample which is a standardsample by using the pretreatment part 20. The operator then sets thesample 20 a prepared by pretreating the standard sample in thefluorescence image analyzer 10, and measures the sample 20 a. Theprocessing part 11 acquires the first to third images for each cell andextracts the region of the nucleus and the region of the bright spot.

As shown in FIG. 5, the processing part 11 then acquires the brightnessof the bright spots in the nucleus from the plurality of first images,and calculates the average brightness of the bright spots of the firstimage based on the acquired brightness of the bright spots. Similarly,the processing part 11 acquires the brightness of the bright spots inthe nucleus from the plurality of second images, and calculates theaverage brightness of the bright spots of the second image based on theacquired brightness of the bright spots. The processing part 11 thencalculates the average brightness of the bright points in all the cellsbased on the average brightness of the first image and the averagebrightness of the second image. Hereinafter, the average brightness ofbright spots in all cells is referred to as the “second index”.

The processing part 11 then compares the threshold value of the warninglevel and the threshold value of the abnormal level with the secondindex to determine whether pretreatment is appropriate. Specifically,when the second index is less than the warning level but equal to ormore than the abnormal level, the processing part 11 determines that thepretreatment state is the warning level, and when the second index isless than the abnormal level, determines that the pretreatment state isthe abnormal level.

Note that, in this case as well, the operator performs pretreatment ofthe negative sample under a plurality of pretreatment conditions inadvance, and when the pretreatment is performed most appropriately, thatis, the case where the value becomes the largest, acquires second index.The operator then presets the threshold of the warning level to a valuethat is smaller than the second index of the largest value by apredetermined value, and presets the threshold of the abnormal level toa value smaller than the value of the warning level.

Note that the second index also may be a value obtained by dividing thenumber of cells including a bright spot with brightness smaller than apredetermined value by the total number of cells. In this case, ifpretreatment is not properly performed, the second index becomes large.Also in the case of using the second index, the appropriateness ofpretreatment can be determined by using the sample 20 a prepared bypretreating the actual sample collected from the subject similar to thefirst index.

Third Index

The third index is an index focusing on the fact that the brightness ofthe bright spots in the first image and the second image decreases andthe S/N ratio based on the first image and the second image decreaseswhen the pretreatment is not properly performed. A procedure foractually determining whether pretreatment is appropriate using the thirdindex is described below.

First, the operator pretreats a negative sample which is a standardsample by using the pretreatment part 20. The operator then sets thesample 20 a prepared by pretreating the standard sample in thefluorescence image analyzer 10, and measures the sample 20 a. Theprocessing part 11 acquires the first to third images for each cell andextracts the region of the nucleus and the region of the bright spot.

As shown in FIG. 6, the processing part 11 then calculates the averagebrightness of the bright spots in the nucleus from the plurality offirst images and the average brightness of the area other than thebright spot area in the nucleus, that is, the background area of thebright spot. Similarly, the processing part 11 acquires the averagebrightness of the bright spots in the nucleus and the average brightnessof the background area of the bright spots from the plurality of secondimages. The processing part 11 calculates the S/N ratio in each image bydividing the average brightness of bright spots by the averagebrightness of the background. The processing part 11 then averages theS/N ratios based on each image and calculates the average S/N ratio inall the cell. Hereinafter, the average S/N ratio in all cells isreferred to as the “third index”.

The processing part 11 then compares the threshold value of the warninglevel and the threshold value of the abnormal level with the third indexto determine whether pretreatment is appropriate. Specifically, when thethird index is less than the warning level but equal to or more than theabnormal level, the processing part 11 determines that the pretreatmentstate is the warning level, and when the third index is less than theabnormal level, determines that the pretreatment state is the abnormallevel.

Note that, in this case as well, the operator performs pretreatment ofthe negative sample under a plurality of pretreatment conditions inadvance, and when the pretreatment is performed most appropriately, thatis, the case where the value becomes the largest, acquires S/N ratio.The operator then presets the threshold of the warning level to a valuethat is smaller than the third index of the largest value by apredetermined value, and presets the threshold of the abnormal level toa value smaller than the value of the warning level.

As shown in FIG. 7, the inventors calculated the average S/N ratio basedon the first image including the green bright spot, and calculated theaverage S/N ratio based on the second image including the red brightspot by changing the heat denaturation temperature and the heatdenaturation time in the pretreatment. In the example shown in FIG. 7,when the heat denaturation temperature is 95° C. and the thermaldenaturation time is 20 minutes, both the average S/N ratio based on thefirst image and the average S/N ratio based on the second image becamehighest. Therefore, when the thermal denaturation temperature is 95° C.and the thermal denaturation time is 20 minutes, that is, when the mostappropriate pretreatment is performed, the third index is approximately385% since the average S/N ratio based on the first image is about 400%and the average S/N ratio based on the second image is about 370%.Therefore, according to the verification result shown in FIG. 7, 250%can be set as the threshold value representing the warning level, and200% can be set as the threshold value representing the abnormal level.

Note that the third index also may be a value obtained by dividing thenumber of cells whose average S/N ratio is smaller than a predeterminedvalue by the total number of cells. In this case, if pretreatment is notproperly performed, the second index becomes large. Also in the case ofusing the third index, the appropriateness of pretreatment can bedetermined by using the sample 20 a prepared by pre-treating the actualsample collected from the subject similar to the first index.

Fourth Index

When the pretreatment is properly performed, a bright spot is imaged asthe state in which fluorescence is generated from one point of thetarget site, and the bright spot on the fluorescence image becomes asubstantially circular shape. On the other hand, as described above,when pretreatment is not performed properly, nonspecific binding occursand fluorescence may be generated from the peripheral portion of thetarget site. The fourth index is an index focusing on the fact that thecircularity of the bright spots in the first image and the second imagedecreases when the preprocessing is not properly performed. A procedurefor actually determining whether pretreatment is appropriate using thefourth index is described below.

First, the operator pretreats a negative sample which is a standardsample by using the pretreatment part 20. The operator then sets thesample 20 a prepared by pretreating the standard sample in thefluorescence image analyzer 10, and measures the sample 20 a. Theprocessing part 11 acquires the first to third images for each cell andextracts the region of the nucleus and the region of the bright spot.

As shown in FIG. 8, the processing part 11 the calculates thecircularity of each bright spot in the nucleus in the first image andthe second image, and determines whether a predetermined number or moreof bright spots whose circularity is lower than a predetermined value,that is, not circular, are present in each cell. In the example shown inFIG. 8, the processing part 11 determines whether there is one or morebright spot having a circularity lower than a predetermined value. Theprocessing part 11 calculates the proportion of cells including a brightspot having a low circularity by dividing the number of cells includingsuch a bright spot having the low circularity by the total number ofcells. Hereinafter, the proportion of cells including bright spots withlow circularity is referred to as the “fourth index”.

The processing part 11 then compares the threshold value of the warninglevel and the threshold value of the abnormal level with the fourthindex to determine whether pretreatment is appropriate. Specifically,when the fourth index is greater than the warning level but less thanthe abnormal level, the processing part 11 determines that thepretreatment state is the warning level, and when the fourth index isgreater than the abnormal level, determines that the pretreatment stateis the abnormal level.

Note that, in this case as well, the operator performs pretreatment ofthe negative sample under a plurality of pretreatment conditions inadvance, and when the pretreatment is performed most appropriately, thatis, the case where the value becomes the smallest, acquires fourthindex. The operator then presets the threshold of the warning level to avalue that is larger than the fourth index of the smallest value by apredetermined value, and presets the threshold of the abnormal level toa value larger than the value of the warning level by a predeterminedvalue.

The fourth index also may be the average of the circularity of all thebright spots in all the cells. In this case, if pretreatment is notproperly performed, the fourth index becomes small. Also in the case ofusing the fourth index, the appropriateness of pretreatment can bedetermined by using the sample 20 a prepared by pre-treating the actualsample collected from the subject similar to the first index.

Fifth Index

As described above, when preprocessing is not performed properly, brightspots may become large due to nonspecific binding. The fifth index is anindex focusing on the fact that the bright spots in the first image andthe second image become larger when the preprocessing is not properlyperformed. A procedure for actually determining whether pretreatment isappropriate using the fifth index is described below.

First, the operator pretreats a negative sample which is a standardsample by using the pretreatment part 20. The operator then sets thesample 20 a prepared by pretreating the standard sample in thefluorescence image analyzer 10, and measures the sample 20 a. Theprocessing part 11 acquires the first to third images for each cell andextracts the region of the nucleus and the region of the bright spot.

As shown in FIG. 9, the processing part 11 the calculates the size ofeach bright spot in the nucleus in the first image and the second image,and determines whether a predetermined number or more of bright spotswhose size is larger than a predetermined value are present in eachcell. In the example shown in FIG. 9, the processing part 11 determineswhether there is one or more bright spot with a size larger than apredetermined value. Note that the size of the bright point is acquiredby the area of the bright spot region in the bright spot image. Theprocessing part 11 calculates the proportion of cells including largebright spots by dividing the number of cells including large brightspots by the total number of cells. Hereinafter, the proportion of cellsincluding large bright spots is referred to as the “fifth index”.

The processing part 11 then compares the threshold value of the warninglevel and the threshold value of the abnormal level with the fifth indexto determine whether pretreatment is appropriate. Specifically, when thefifth index is greater than the warning level but less than the abnormallevel, the processing part 11 determines that the pretreatment state isthe warning level, and when the fifth index is greater than the abnormallevel, determines that the pretreatment state is the abnormal level.

Note that, in this case as well, the operator performs pretreatment ofthe negative sample under a plurality of pretreatment conditions inadvance, and when the pretreatment is performed most appropriately, thatis, the case where the value becomes the smallest, acquires fifth index.The operator then presets the threshold of the warning level to a valuethat is larger than the fifth index of the smallest value by apredetermined value, and presets the threshold of the abnormal level toa value larger than the value of the warning level by a predeterminedvalue.

Note that the fifth index also may be the average size of all the brightspots in all the cells. In this case, if pretreatment is not properlyperformed, the fifth index becomes large. Also in the case of using thefifth index, the appropriateness of pretreatment can be determined byusing the sample 20 a prepared by pre-treating the actual samplecollected from the subject similar to the first index.

Sixth Index

As described above, when pretreatment is not properly performed, thetarget site may be insufficiently fluorescently labeled in some cases.The sixth index is an index focusing on the fact that the number of thebright spots in the first image and the second image decreases when thepreprocessing is not properly performed.

First, the operator pretreats a negative sample which is a standardsample by using the pretreatment part 20. The operator then sets thesample 20 a prepared by pretreating the standard sample in thefluorescence image analyzer 10, and measures the sample 20 a. Theprocessing part 11 acquires the first to third images for each cell andextracts the region of the nucleus and the region of the bright spot.

As shown in FIG. 10, the processing unit 11 then calculates the numberof bright spots in the nucleus in the first image and the second image.Then, the processing part 11 averages the number of bright spots basedon each image, and calculates the average value of the bright spots inall the cells. Hereinafter, the average value of the number of brightspots in all cells is referred to as the “sixth index”.

The processing part 11 then compares the threshold value of the warninglevel and the threshold value of the abnormal level with the sixth indexto determine whether pretreatment is appropriate. Specifically, when thesixth index is less than the warning level but equal to or more than theabnormal level, the processing part 11 determines that the pretreatmentstate is the warning level, and when the sixth index is less than theabnormal level, determines that the pretreatment state is the abnormallevel. Note that in this case, if pretreatment is not properlyperformed, the value of the sixth index becomes 2. The operator thenpresets the threshold of the warning level to a value that is smallerthan 2 by a predetermined value, and presets the threshold of theabnormal level to a value smaller than the value of the warning level.

Note that the sixth index may be the degree of divergence from 2 whichis the ideal value when the pretreatment is appropriately performed. Inthis case, if pretreatment is not properly performed, the sixth indexbecomes large. The sixth index may be a value obtained by dividing thenumber of cells with fewer than two bright spots by the total number ofcells. In this case, if pretreatment is not properly performed, thesixth index becomes large.

Also in the case of using the sixth index, the appropriateness ofpretreatment can be determined by using the sample 20 a prepared bypre-treating the actual sample collected from the subject similar to thefirst index. In this case, since positive cells may be mixed in thesample, the ideal value of the sixth index when the pretreatment isproperly performed is slightly larger than 2. However, in considerationof the probability that a positive cell actually exists, it is possibleto use a threshold value of the warning level and a threshold value ofthe abnormal level similar to those based on a negative cell asdescribed above.

Note that although the first to sixth indices are calculated based onboth the first image and the second image, the indices also may becalculated from either one of the fluorescence images.

Embodiments 1 to 7 in which pretreatment appropriateness is determinedusing the first to sixth indices, and abnormal cells are detected byanalyzing a sample are described below. The fluorescence image analyzer10 and the pretreatment part 20 shown in FIG. 1 are used in embodiments1 to 7, unless otherwise mentioned.

First Embodiment

As shown in FIG. 11A, in step S11, the pretreatment part 20 pre-treats anegative sample as a standard sample to prepare a sample 20 a. Step S11includes a step of hybridizing a nucleic acid probe labeled with thefluorescent dye and the BCR region and the ABL region in the nucleicacid of the negative sample. In step S12, the processing part 11measures the sample 20 a prepared in the pretreatment in step S11.Specifically, the processing part 11 causes the sample 20 a preparedfrom a negative sample to flow through the flow path 111 of the flowcell 110, irradiates the flow path 111 with light from the light sources121 to 124, and captures the fluorescence generated from the sample 20 aand the light transmitted through the sample 20 a via the imaging part154 to acquire the first to third images and a bright field image. Theprocessing part 11 stores the first to third images and the bright fieldimage in the memory part 12.

In step S13, the processing part 11 acquires the first to sixth indicesand the determination result of whether pretreatment is appropriate isacquired as information based on the index. Specifically, the processingpart 11 extracts the region of the nucleus and the region of the brightspot based on the first to third images. As described above, theprocessing part 11 then calculates the first to sixth indices, anddetermines whether pretreatment is appropriate based on the calculatedfirst to sixth indices. The warning level threshold value and theabnormal level threshold value used for the determination based on thefirst to sixth indices are stored in the memory part 12. The processingpart 11 stores the values of the first to sixth indices and thedetermination results based on the first to sixth indicators in thememory part 12. In step S14, the processing part 11 displays informationbased on the index on the display part 13. Specifically, the processingpart 11 displays on the display part 13 a screen 210 including thedetermination result and the first to sixth indices acquired in stepS13.

As shown in FIG. 11B, the screen 210 displays the values of the first tosixth indices and the determination results based on the first to sixthindices, respectively. When the screen 210 is configured in this way,the operator can determine whether pretreatment has been appropriatelyperformed based on each index. If the operator determines that thepretreatment was inappropriate, the operator can take measures such asreviewing each process included in the pretreatment and performingpretreatment again. When the operator determines that the pretreatmentis appropriate, the operator analyzes the actual sample collected fromthe subject, as shown in FIG. 12A.

As shown in FIG. 12A, in step S21, the pretreatment part 20 performspretreatment on the sample collected from subject and that has beensubjected to processing such as centrifugation to prepare sample 20 a,as in step S11 of FIG. 11A. In step S22, the processing part 11 measuresthe sample 20 a prepared by the pretreatment of step S21 in the samemanner as in step S12 of FIG. 11A.

In step S23, the processing part 11 performs analysis. Specifically,based on the first to third images, the processing part 11 counts thecells whose bright spots are negative patterns shown in FIG. 3A, thatis, negative cells. The processing part 11 also counts the cells inwhich the bright spots are any of the positive patterns 1 to 3 shown inFIGS. 3B to 3D, that is, positive cells, based on the first to thirdimages. The processing part 11 also calculates the ratio of positivecells to all cells by dividing the number of positive cells by the totalnumber of cells. In step S24, the processing part 11 displays the screen220 including the analysis result acquired in step S23 on the displayunit 13.

As shown in FIG. 12B, the screen 220 displays the sample ID foridentifying the sample, the number of positive cells, the number ofnegative cells, and the ratio of positive cells to all cells. When thescreen 220 is configured as described above, the physician or the likecan use the display content of the screen 220 for determining whetherthe sample is positive or negative. Note that when the proportion ofpositive cells exceeds a predetermined threshold value, the processingpart 11 also may display, for example, “Potentially Positive?” tosuggest the sample is positive.

Note that in step S13 the processing part 11 calculates the first tosixth indices without performing the determination regarding theappropriateness of the pretreatment, and displays the screen 210including only the values of the first to the sixth indices on thedisplay part 13 in step S14. In this case, for example, the operatorchecks the values of the first to sixth indices and determines whetherthe pretreatment is appropriate.

Second Embodiment

In the second embodiment, pretreatment is performed on the actual samplecollected from the subject, and the appropriateness of the pretreatmentis determined based on the sample 20 a prepared from the actualpretreated sample.

As shown in FIG. 13A, in step S31, the pretreatment part 20 performs aprocess on the sample collected from the subject and that has beensubjected to a process such as centrifugation to prepare sample 20 a, asin step S21 of FIG. 12A. In step S32, the processing part 11 measuresthe sample 20 a prepared by the pretreatment of step S31 in the samemanner as in step S12 of FIG. 11A.

In step S33, the processing part 11 acquires information based on theindex in the same manner as in step S13 of FIG. 11A, and performsanalysis similarly to step S23 of FIG. 12A.) In step S34, the processingpart 11 displays the information based on the index on the display part13 in the same manner as in step S14 of FIG. 11A, and outputs theanalysis result to the display part 13 as in step S24 of FIG. 12A.Specifically, in step S34, the processing part 11 displays the screen230 including the index, the determination result, and the analysisresult on the display part 13.

As shown in FIG. 13B, the screen 230 displays the values of the first tosixth indices, the determination results based on the first to sixthindices, the sample ID for identifying the sample, the number ofpositive cells, the number of negative cells, and the proportion ofpositive cells to all cells. When the screen 230 is configured in thismanner, the physician or the like can determine whether the sample ispositive or negative while checking appropriateness of pretreatment ofthe sample. For example, when the determination result of thepretreatment is appropriate, the physician or the like determines thatthe reliability of the analysis result is high and can diagnose thesample with high accuracy. On the other hand, if the determinationresult of the pretreatment is inappropriate, the physician or the likecan determine that the reliability of the analysis result is low andtake measures such as suspending the diagnosis of the sample. Inaddition, it is not necessary to use a standard sample for determiningpretreatment appropriateness.

Note that in step S33 the processing part 11 calculates the first tosixth indices without performing the determination regarding theappropriateness of the pretreatment, and displays the screen 230including the values of the first to the sixth indices and the analysisresults on the display part 13 in step S34.

Third Embodiment

In the third embodiment, similarly to the second embodiment,pretreatment is performed on the actual sample collected from thesubject to determine whether pretreatment is appropriate. In the thirdembodiment, first to sixth indicators in a predetermined period arecalculated, and pretreatment appropriateness is determined.

Every time pretreatment is performed, the processing part 11 stores thedate and time when the pretreatment was performed, the sample ID, thefirst to third images, and the bright field image as information relatedto the bright spot in the database 12 a. Database 12 a is stored in thememory part 12. Note that the processing part 11 extracts the region ofthe bright spot, the brightness of the bright spot, and the backgroundregion from the first to the third images, and stores the extractedinformation as information related to the bright spot in the database 12a.

Every time pretreatment is performed, the processing part 11 acquiresthe first to sixth indices based on the first to third images, displaysthe acquired first to sixth indices as shown in FIG. 14B, and stores theindices in the database 12 b. That is, the processing part 11 acquiresthe first to sixth indices for each sample 20 prepared by pretreatment,and stores the obtained first to sixth indices in the database 12 b inassociation with the sample 20 a. Database 12 b is stored in the memorypart 12. The processing part 11 also may store the determination resultsbased on the first to sixth indices in the database 12 b. When the firstto sixth indices are stored for each sample 20 a in this manner, theprocessing part 11 can smoothly display the first to sixth indices onthe display part 13 for the pretreatments performed in the past. Notethat the processing part 11 also may store the first to sixth indices inthe database 12 b with a predetermined timing, for example, with thetiming when the analyses of one day is completed.

As shown in FIG. 15A, in step S41, the processing part 11 receives theperiod input by the operator via the input part 14. The period consistsof the start date and time and the end date and time.

In step S42, the processing part 11 acquires information based on theindex within the period based on the first to third images included inthe period received in step S41 from the database 12 a shown in FIG.14A. Specifically, the processing part 11 calculates first to sixthindices in the same manner as described above based on all the first tothird images included in the reception period, and determines whetherpretreatment is appropriate as described above based on the calculatedfirst to sixth indices. Note that the processing part 11 also mayacquire the first to sixth indices of the reception period by averagingthe same indices included in the reception period based on the database12 b shown in FIG. 14B. Good In step S43, the processing part 11displays on the display part 13 a screen 240 including information basedon the indices acquired in step S42, that is, a screen 240 includingfirst to sixth indices, and the determination results of whetherpretreatment is appropriate.

As shown in FIG. 15B, the screen 240 displays the period input by theoperator, the first to sixth indices of the reception period, and thedetermination results based on the first to sixth indices. When thescreen 240 is configured in this manner, the operator can know the firstto sixth indices and the determination result of the pretreatmentappropriateness in a predetermined time span. In the example shown inFIG. 15B, the operator can know the index and the judgment result on theday of “May 10, 2016”.

Note that in step S42 the processing part 11 calculates the first tosixth indices without performing the determination regarding theappropriateness of the pretreatment, and displays the screen 240including only the values of the first to the sixth indices on thedisplay part 13 in step S43. In step S 41, although the processing part11 also acquires and displays information based on the index based onthe period input by the operator, the processing part 11 also mayautomatically set the time 0 to 24 as one day in accordance with to theoperator's start instruction.

Fourth Embodiment

In the fourth embodiment, the time course of the index is graphicallydisplayed additionally in the third embodiment.

As shown in FIG. 16A, in step S51, the processing part 11 receives theperiod, display unit, and selected index input by the operator via theinput part 14. As in the third embodiment, the period includes the startdate and time and the end date and time. The display unit is the timespan of one day, one hour, and the like. The selected index is one ofthe first to sixth indices.

In step S52, the processing part 11 acquires information based on theselected index of each display unit based on all the first to thirdimages included in the period received in step S51 from the database 12a shown in FIG. 14A. For example, when the display unit is one day andthe selected index is the first index, the processing part 11 acquiresthe first index of each day and the pretreatment determination resultbased on the first index within the period. Note that the processingpart 11 also may acquire information based on the selected index foreach display unit within the period based on the database 12 b shown inFIG. 14B. In step S53, the processing part 11 displays the screen 250including the graph based on information acquired in step S52 on thedisplay unit 13.

As shown in FIG. 16B, the screen 250 displays an area for displaying theperiod, display unit, and selected index input by the operator, and agraph based on the information acquired in step S52. In the exampleshown in FIG. 16B, the temporal transition of the first index each dayfor 10 days is shown on the graph, and the graph shows the warning leveland the abnormal level together. When the screen 250 is configured inthis manner, the operator can visually comprehend the temporaltransition of the first to sixth indices within a predetermined period,so that the state of the pretreatment can be more accurately grasped.

Note that although the processing part 11 creates a graph based on theinformation input by the operator in step S51, the processing part 11also may automatically set the display unit as one day and set theperiod as 10 days from the current day. The processing part 11 also maydisplay six graphs based on the first to sixth indices on the screen 250without receiving a selected index. The processing part 11 also maydisplay the value of the index at each point in the graph.

Fifth Embodiment

In the fifth embodiment, instead of the screen 210 of the firstembodiment shown in FIG. 11B, the screen 260 shown in FIG. 17 isdisplayed on the display part 13. As shown in FIG. 17, the screen 260displays, in addition to the first to sixth indices and thedetermination result, a radar chart visually showing the correlationbetween the first to the sixth indices. Note that in this case eachindex is calculated so that plotted points move outward as the values ofthe first to sixth indices increase. For example, although the fourthindex is the proportion of cells including bright spots with lowcircularity, the fourth index in this case is the proportion of cellsthat do not contain bright spots with low circularity.

When the screen 260 is configured in this way, the operator can visuallygrasp the correlation between the first to the sixth indices. Note thatthe radar chart shown in FIG. 17 also may be displayed in the screen 230of the second embodiment shown in FIG. 13B.

Sixth Embodiment

As shown in FIG. 18, the fluorescence image analyzer 10 of the sixthembodiment includes an imaging unit 300 including a fluorescencemicroscope in place of the imaging unit 100 shown in FIG. 1. In otherrespects the configuration of the sixth embodiment is the same as theconfiguration shown in FIG. 1.

The imaging unit 300 includes light sources 301 to 303, a mirror 304,dichroic mirrors 305 and 306, a shutter 311, a quarter-wave plate 312, abeam expander 313, a condenser lens 314, a dichroic mirror 315, anobjective lens 316, a stage 320, a condenser lens 331, an imaging part332, and controllers 341 and 342. A slide glass 321 is placed on thestage 320. The sample 20 a prepared by the pretreatment via thepretreatment part 20 is placed on the slide glass 321.

The light sources 301 to 303 are respectively identical to the lightsources 121 to 123 shown in FIG. 1. The mirror 304 reflects the lightfrom the light source 301. The dichroic mirror 305 transmits the lightfrom the light source 301 and reflects the light from the light source302. The dichroic mirror 306 transmits the light from the light sources301 and 302, and reflects the light from the light source 303. Theoptical axes of the light from the light sources 301 to 303 are made tocoincide with each other by the mirror 304 and the dichroic mirrors 305and 306.

The shutter 311 is driven by the controller 341 to switch between astate of passing light emitted from the light sources 301 to 303 and astate of blocking light emitted from the light sources 301 to 303. Inthis way the irradiation time of light to the sample 20 a is adjusted.The quarter-wavelength plate 312 converts the linearly polarized lightemitted from the light sources 301 to 303 into circularly polarizedlight. Fluorescent dye bound to the nucleic acid probe reacts to lightof a predetermined polarization direction. Therefore, by converting theexcitation light emitted from the light sources 301 to 303 intocircularly polarized light, the polarization direction of the excitationlight easily coincides with the polarization direction in which thefluorescent dye reacts. In this way it is possible to efficiently excitethe fluorescent dye to fluorescence. The beam expander 313 broadens theirradiation region of the light on the slide glass 321. The condenserlens 314 condenses the light from the objective lens 316 so as toirradiate parallel rays on the slide glass 321.

The dichroic mirror 315 reflects light emitted from the light sources301 to 303, and transmits fluorescent light given off from the sample 20a. The objective lens 316 directs the light reflected by the dichroicmirror 315 to the slide glass 321. The stage 320 is driven by thecontroller 342. Fluorescent light given off from the sample 20 a passesthrough the objective lens 316 and passes through the dichroic mirror315. The condenser lens 331 collects the fluorescent light transmittedthrough the dichroic mirror 315 and directs the light to the imagingsurface 332 a of the imaging part 332. The imaging part 332 captures animage of the fluorescent light irradiated on the imaging surface 332 ato generate a fluorescence image. The imaging part 332 is configured,for example, by a CCD or the like.

The controllers 341 and 342 and the imaging part 332 are connected tothe processing part 11 shown in FIG. 1, and the processing part 11controls the controllers 341 and 342 and the imaging part 332, andreceives the fluorescence image captured by the imaging part 332. Asshown in FIG. 1, the fluorescent image captured by the imaging part 332may be in a state of close contact with the cell as shown in FIG. 2Aunlike the case where the flow cell 110 is used. Therefore, theprocessing part 11 performs a process of dividing the obtainedfluorescence image for each nucleus of a cell, or a process of setting aregion corresponding to one nucleus of a cell in the fluorescence imageor the like.

In the sixth embodiment as in the other embodiments, the first to thesixth indices are acquired based on the first to third images since thefirst to third images can be acquired, and it is possible to determinewhether pretreatment is appropriate based on the acquired first to sixthindices.

Seventh Embodiment

As shown in FIG. 19, the fluorescence image analyzer 10 of the seventhembodiment includes the pretreatment part 20 shown in FIG. 1. Theprocessing part 11 is connected to the pretreatment part 20, receivessignals from the pretreatment part 20, and controls the pretreatmentpart 20. When the pretreatment part 20 receives the sample 10 acollected from a subject and that has been processed by centrifugationor the like, the pretreatment part 20 performs pretreatment on thesample 10 a to prepare the sample 20 a. The imaging unit 100 measuresthe sample 20 a prepared by the pretreatment part 20, and acquires thefirst to third fluorescence images and the bright field image. In otherrespects the configuration of the seventh embodiment is the same as theconfiguration shown in FIG. 1.

When the fluorescence image analyzer 10 includes the pretreatment part20 as described above, the operator automatically performs thepretreatment merely by setting the sample 10 a in the fluorescence imageanalyzer 10, and the sample 20 a is prepared by the pretreatment isautomatically analyzed. The processing part 11 also acquires the firstto sixth indices, and determines whether pretreatment by thepretreatment part 20 is appropriate. In this way the operator can graspwhether the pretreatment was appropriate in the analysis of the sampleautomatically performed by the fluorescence image analyzer 10.

Eighth Embodiment

As shown in FIG. 20, the memory part 12 of the eighth embodiment storesbright spot patterns for determining whether a cell is positive ornegative. The bright spot pattern of FIG. 20A shows the state of brightspots in the fluorescence image exemplified in FIGS. 3A to 3D. In thepattern of the bright spot shown in FIG. 20A, “G” represents the greenbright spot in the first image, “R” represents the red bright spot inthe second image, “F” represents the fusion bright spot, that is, ayellow bright spot in the composite image. The numbers immediatelyfollowing G, R, F indicate the number of bright spots of G, R, and F,respectively. For example, in the case of “G 2 R 2 F 0”, the number ofgreen bright spots in the first image is two, the number of red brightspots in the second image is two, and the number of yellow bright spotsin the composite image is zero respectively.

Note that G also may represent the green bright spot of the compositeimage and R may represent the red bright spot in the composite image. Inthis case, the patterns of the bright spots shown in the 1st to 4th rowsin FIG. 20A are “G 2 R 2 F 0”, “G 1 R 2 F 1”, “G 1 R 1 F 2”, and “G 1 R1 F 1”.

The patterns of the bright spots shown in the first to fourth rows ofFIG. 20A correspond to the bright spots of the fluorescence images shownin FIGS. 3A to 3D, respectively. The pattern based on the bright spotshown in FIG. 20A is associated with a determination based on thepattern of the bright spot. For example, “negative” is associated withthe pattern of the bright spot in the first row, and “positive” isassociated with the pattern of the bright spot in the second row. Notethat the memory part 12 stores not only the patterns of the four brightspots shown in FIG. 20A but also a plurality of possible combinationsthereof.

In the eighth embodiment, the same processing is performed as that ofthe first embodiment shown in FIG. 12A. A process different from that ofthe first embodiment will be described below.

In step S23, the processing part 11 extracts bright points from thefluorescence image for each of the plurality of cells included in thesample 20 a in the same manner as the procedure described with referenceto FIGS. 2A to 2D. Then, the processing part 11 classifies each of theplurality of cells based on the pattern of the bright spots, and theprocessing part 11 generates information used for determining whetherthe sample 20 a is positive or negative based on the classificationresults of the plurality of cells.

Specifically, in step S23, the processing part 11 compares the patternof the bright spot of the cell with the patterns of the bright spotstored in the memory part 12 shown in FIG. 20A, and determines whetherthe cell is positive or negative for each cell of the plurality ofcells. When the bright spot pattern of the cell matches the positivepattern, the processing part 11 determines that the cell is positive,and when the bright spot pattern of the cell matches the negativepattern, the processing part 11 determines that the cell is negative.The processing part 11 then generates the number of positive cells, thenumber of negative cells, the ratio of the number of positive cells tothe number of detected cells, the ratio of the number of negative cellsto the number of detected cells, information on a pattern determinedbased on the number and color of bright spots, and informationsuggesting whether the sample 20 a is positive or negative. Theinformation generated in step S23 will be described later with referenceto FIG. 20B.

In step S24, the processing part 11 displays the screen 221 includingthe information generated in step S23 on the display part 13. As shownin FIG. 20B, the display content on the screen 221 is invariablyinformation used for determining whether the sample 20 a is positive ornegative.

As shown in FIG. 20B, the information related to the pattern determinedon the basis of the number and the color of the bright spots includesthe pattern of the bright spot shown in FIG. 20A, the number of cellsmatching this bright spot pattern, and the proportion of cells matchingthe bright spot pattern relative to the total number of cells. In thisway the information related to the pattern determined based on thenumber and the color of the bright spots includes the result ofclassifying each of the plurality of cells based on the pattern of thebright spots.

In the case where the screen 221 shown in FIG. 20B is displayed, thepattern of the bright spot considered as positive is selected in advancefrom the positive bright spot pattern shown in FIG. 20A. Then, the cellsthat match the selected positive bright spot pattern are determined tobe positive. The number of positive cells displayed on the screen 221 isthe number of cells matching the selected positive bright spot pattern.Therefore, assuming that the number of negative cells is N1 and thenumber of positive cells in this case is N2, the proportion of positivecells is obtained by dividing N2 by N1+N2, and the proportion ofnegative cells is obtained by dividing N1 by N1+N2.

Information indicating whether the sample 20 a is positive or negativeis composed of character information such as “potentially positive?” or“potentially negative?” and the like. For example, when the proportionof positive cells is larger than a predetermined threshold value or theratio of negative cells is smaller than a predetermined threshold value,“potentially positive?” is displayed. When the proportion of negativecells is larger than a predetermined threshold value or the proportionof positive cells is smaller than a predetermined threshold value,“potentially negative?” is displayed. The display may not be performedinstead of “potentially negative?”. Information based on the index alsomay be displayed together in screen 221 similarly to FIG. 13B.

According to the eighth embodiment, the physician or the like can referto the display contents of the screen 221, and can highly accuratelydetermine whether the sample 20 a and sample that is the basis of sample20 a is positive or negative.

Other Embodiments

In the above-described embodiments, the target site is the BCR gene andthe ABL gene, but the present invention is not limited to thisconfiguration inasmuch as other target gene regions may also be used. Inthe case of chronic myelogenous leukemia, translocation may occur in theBCR gene and the ABL gene, but abnormality similarly may be found inspecific gene regions even in specific diseases. In the case where thetarget site is another gene region, the processing part 11 calculatesthe proportion of the number of positive cells related to a specificdisease or the number of positive cells to the number of detected cells,and displays the calculated number or proportion on the display part 13as the analysis result. Also in this case, as in the eighth embodiment,the processing part 11 generates information used for determiningwhether the sample 20 a is positive or negative as shown in FIG. 20B,and displays the generated information on the display part 13.

The target site may be, for example, the HER2 gene and CEP17, which is acentromere region of chromosome 17. The HER2 gene is amplified inassociation with cell carcinogenesis, and CEP17 does not amplify inconjunction with cell carcinogenesis. Therefore, when the HER2 gene andCEP17 are used as the target site, it is possible to determine theappropriateness of pretreatment on the basis of the sample 20 a preparedby pretreating the negative sample. That is, in the case of a negativesample, it is possible to determine the appropriateness of thepretreatment based on the fact that there are two bright spots of theHER2 gene and two bright spots of the CEP17 in the nucleus. In addition,when an actual sample collected from a subject is used to determinewhether pretreatment is appropriate, the determination of pretreatmentappropriateness can be made based on bright spots of CEP17.

Also, the target site is not limited to nucleic acids, but may besubstances other than cells on the cell surface and the like. Labelingof the target site is not limited to hybridization and also may beperformed by antigen-antibody reaction. Further, the pretreatment part20 may be configured to automatically perform processes such ascentrifugation. The sample to be pretreated by the pretreatment part 20is not limited to a blood sample, and may be, for example, a plasmasample or a sample collected from diseased tissue or the like. Cells tobe analyzed are not limited to white blood cells, and may be, forexample, epithelial cells.

What is claimed is:
 1. A method for analyzing a sample treated with afluorescent label specifically biding to a target site of a cell,comprising: forming a flow of a sample in a flow cell; irradiating lighton the sample running in the flow cell; capturing fluorescence images ofindividual cells irradiated by light; and digitally analyzing a patternof bright spots in each individual cell of at least some of theindividual cells in at least some of the fluorescence images to identifyat least a positive cell having a particular pattern of bright spotsbased on a color and a number of bright spots, wherein a positive cellis distinguishable from a negative cell according to the pattern ofbright spots.
 2. The method of claim 1, further comprising generatinginformation of any one selected from a group consisting of: a number ofpositive cells, a number of negative cells, a ratio of the number ofpositive cells to the number of negative cells, and a ratio of thenumber of negative cells to the number of positive cells.
 3. The methodof claim 1, further comprising generating information of a population ofpositive cells in the sample.
 4. The method of claim 1, wherein a firstimage at a first wavelength and a second image at a second wavelengthare captured, in the capturing; the method further comprising mappingbright spots based on the first and second images.
 5. The method ofclaim 1, further comprising acquiring an index that is indicative of anappropriateness of a pretreatment.
 6. The method of claim 5, wherein theindex is a ratio of a first number to a second number, the first numberrepresenting a number of detected cells through the flow cell and thesecond number representing a number of cells for which a fluorescentimage is to be digitally analyzed.
 7. The method of claim 5, wherein theindex is a brightness of at least one bright spot.
 8. The method ofclaim 5, wherein the index is a ratio between a brightness of at leastone bright spot and a brightness of a background area of the cell. 9.The method of claim 5, wherein the index is a shape of at least onebright spot.
 10. The method of claim 5, wherein the index is a size ofat least one bright spot.
 11. The method of claim 5, wherein the indexis a number of bright spots.
 12. The method of claim 5, furthercomprising displaying, on a display, that a pretreatment is appropriatewhen the index meets a criteria.
 13. The method of claim 5, furthercomprising measuring a standard sample to acquire the index, anddisplaying information whether pretreatment is appropriate in referenceto the acquired index.
 14. A method for analyzing a sample, comprising:hybridizing a nucleic acid of cells in a sample and afluorescent-labeled probe; forming a flow of the sample in a flow cell;irradiating light on the sample running in the flow cell; capturingfluorescence images of individual cells irradiated by light; digitallyanalyzing at least some of the fluorescence images to extract brightspots in each individual cell of at least some the individual cells; andidentifying, based on a number and a color of the bright spots,particular individual cells having a translocation of a target site. 15.The method of claim 14, wherein a number and a color of bright spots inthe at least one of the fluorescence images varies according to atranslocation of the target site.
 16. The method of claim 14, furthercomprising generating information of a population of the particularcells in the sample.
 17. A sample analyzer comprising: a flow cellconfigured to receive a sample to run through; a light source configuredto irradiate light on the sample running through the flow cell; animaging device configured to capture fluorescence images of individualcells in the sample irradiated by light; and a processor configured todigitally analyzing a pattern of bright spots in each individual cell ofat least some of the individual cells in at least some of thefluorescence images and identify at least a positive cell having aparticular pattern of bright spots based on a color and a number ofbright spots, wherein a positive cell is distinguishable from a negativecell according to the pattern of bright spots.
 18. A method foranalyzing a sample treated with a fluorescent label specifically bidingto a target site of a cell, comprising: forming a flow of a sample in aflow cell; irradiating light on the sample running in the flow cell;capturing fluorescence images of individual cells irradiated by light;digitally analyzing a pattern of bright spots in the individual cell inthe fluorescence image; and classifying, based on a color and a numberof bright spots, the individual cells into at least two groups includingpositive cells and negative cells.